text:
|Numéro de publication
|Type de publication
|Numéro de demande
|Date de publication
|10 févr. 1998
|Date de dépôt
|15 mars 1995
|Date de priorité
|15 mars 1995
|État de paiement des frais
|Numéro de publication
|Martin Rothenberg
|Cessionnaire d'origine
|Syracuse Language Systems
|Exporter la citation
|BiBTeX, EndNote, RefMan
|Citations de brevets (21), Citations hors brevets (16), Référencé par (91), Classifications (12), Événements juridiques (6)
|Liens externes: USPTO, Cession USPTO, Espacenet
1. Field of the Invention
This invention relates to a speech recognition apparatus and method. More precisely, this invention relates to a speech recognition apparatus and method useful for both whole-word/phrase understanding and pronunciation correction to enable oral language learning.
2. Description of the Related Technology
Modern multimedia computers can be an effective tool for learning new language skills. Still and animated visual images, text, and audio can be interwoven in interactive programs. The audio may include both computer-generated (synthesized) speech or large amounts of high quality natural speech, prerecorded and stored efficiently in digital form, and accessed as required for the interactive learning program. The weak link, however, is the ability of a computer to accept and act differentially in response to the speech of a learner in an interactive language learning application.
Even the most powerful computer is still unable to analyze the meaning, syntax, and pronunciation of a user's unrestricted continuous speech in near-real time, as does the human auditory system. Compared to the human capability, the abilities of the best computers (even without the real-time restriction needed for interactive situations) are extremely rudimentary. Various articles have been written that describe the inadequacy of various speech recognition systems, including Richard D. Peacocke & Daryl H. Graf, An Introduction to Speech and Speaker Recognition, COMPUTER Magazine, August 1990, at 26-34; David B. Roe & Jay G. Wilpon, Whither Speech Recognition: The Next 25 Years, IEEE Communications Magazine, November 1993, at 54-62; Alexander I. Rudnicky, et al., Survey of Current Speech Technology, Communications of the ACN, March 1994, at 52-56.
However, there are many computer-based systems for accepting and acting differentially in response to human speech that emulate enough of the human capability to be useful in specific applications. Among these are "speech understanding" systems which are directed towards identification of the intended meaning or semantic content of an input segment of speech. Speech understanding systems may be useful, for example, in task-oriented human-computer interactions in which it is not important to identify the actual words spoken or obtain an analysis of the syntax or pronunciation of the speech. See U.S. Pat. No. 5,357,596 and Hirohjuki Tsuboi, et al., Real-Time Task-Oriented Speech Understanding System Using Keyword Spotting, IEEE Transactions on Acoustical Speech and Signal Processing, September 1992, at 197-200.
There are other applications, such as automated dictation or voice data entry, for which it is important for a computer to identify the actual words spoken. Systems accepting speech input that emphasize the correct identification of particular words or sequences of words are commonly referred to as "speech recognition" systems, or "word recognition" systems if the speech input segments are limited to single words or short phrases. (Unfortunately, the term "speech recognition" is also used loosely as a descriptive label for the totality of systems accepting and selectively acting in response to speech input.) For example, in a system for automated dictation for English, it is of primary importance to obtain the correct orthographic representation of a spoken word, and meaning is secondary. If the spoken sentence is "He's a bear of a man," or "He will bear the burden," the semantic content of "bear" is only important to the extent that it is not transcribed "bare." In "He tore across the room," the word "tore", to a speech understanding system, must be unambiguously understood as "moved quickly," whereas to a speech recognition system for dictation it is merely the word that happens to be the past tense of "tear."
A third type of system accepting and selectively responding to a speech input can be termed a "speech analysis" system. Speech analysis systems are used in applications in which properly and improperly formed or pronounced speech must be differentiated, whereas speech recognition and speech understanding systems are primarily directed, respectively, to determining the intended linguistic segments or the intended semantic content relative to a specific context or task to be performed.
To be maximally useful for language instruction, a system for interactive human-computer speech communication must be able to exhibit all three of these capabilities of a human tutor familiar with the language: understanding, segment recognition, and speech pattern analysis. To accomplish this, there would have to be either a very significant improvement in the capabilities of present speech input technology or the devising of a system for human-computer speech interaction in which a speech input technology that is constructed according to the present state-of-the-art can be used. This invention is directed toward the latter approach.
Among the attempts to create a restricted emulation of this human speech recognition capability, there is presently a technology available for speech input to a computer that is constructed so as to automatically determine which of a pre-specified, finite number of speech segments was spoken. A software package, or a combination of software and hardware, designed to accomplish this task can be referred to as a discrete speech recognition engine ("DSRE"). This type of system has been applied to purposes such as voice data entry and providing voice control over some of the functions of a computer or voice control over the functions of a system operated under the control of a computer. In another application, a DSRE with a large vocabulary can be used for dictation, if the words are spoken separately with a short pause after each word. This capability is often referred to as discrete speech recognition.
A DSRE contains a computer program that accepts a sample digitized speech waveform X, and compares it to a preset number N of waveforms, information about which is stored in computer memory. The DSRE computer program may calculate a number, or set of numbers, that reflects the similarity of the sample waveform X to each of the N internally stored waveforms according to an analysis scheme used by the computer program. This calculated number is often referred to as a distance measure. The "distances" between the sample waveform X and each of the N internal waveforms may then be represented by an array X, Ai!, where i varies from one to N. The computer program can produce all of the distance measures between the sample waveform and the internal waveforms and determine the internal waveform yielding the best match (having the smallest distance measure) to the sample waveform X, or determine that no internal sample was a good enough match, according to criteria set by the computer program or the user.
Internal waveforms can be formed so as to enable a DSRE to accept a wide range of voices as matching, thus making the matching process speaker-independent to a greater or lesser degree. Conversely, a DSRE that derives its internal waveforms only from examples of the voice of the user is well suited primarily to that one person and may be highly speaker-dependent. In practice, however, there is no clear line between speaker-dependent and speaker-independent, because a DSRE designed to be speaker-dependent may work well with other speakers having speech characteristics similar to those of the intended user, and a DSRE designed to be speaker-independent may often require optimization for individual speakers having voices or speech characteristics far from the expected norm (such as young children, speakers having a strong regional or cultural dialect or foreign accent, or speakers having a partially dysfunctional voice as a result of illness).
There are a number of modifications of the basic scheme for discrete speech recognition that are intended to increase its scope or capabilities. In an adaptive DSRE, the performance of a speaker-independent system is optimized by having the system automatically incorporate information about the user's speech characteristics while the system is being used. Such a system is described in Paul Barnberg, et al., Phoneme-Based Training for Large-Vocabulary Recognition in Six European Languages, Proc. of the Second Eur. Conf. on Speech Comm. and Tech. (Geneva), September 1991, at 175-81. An adaptive system can be `broadly adaptive` if it only identifies and adapts to a large class of speakers to which the speaker belongs (male vs. female; American English speaker vs. British English speaker) or `narrowly adaptive` if it adapts to the detailed speech characteristics of the speaker.
In another modification of the basic scheme, to reduce the number of internal models that must be stored in the computer as the vocabulary is increased, models for reoccurring parts of a word, such as the phonemes (letter-sounds, to a first approximation) or short phoneme sequences, are stored, and complete words or phrase models are constructed from these segment models. There is generally a resulting decrease in recognition accuracy which may be acceptable in some applications. Paul Bamberg, et al., Phoneme-Based Training for Large-Vocabula Recognition in Six European Languages, Proc. of the Second Eur. Conf. on Speech Comm. and Tech. (Geneva), September 1991, at 175-81; Kai-Fu Lee, Context-Dependent Phonetic Hidden Markov Models for Speaker-Independent Continuous Speech Recognition, IEEE Transactions on Acoustical Speech and Signal Processing, April 1990, at 599-609. Some commercial DSREs include both whole-word/phrase models and constructed models. See U.S. Pat. No. 5,315,689.
In yet another modification, often referred to as `word-spotting`, the DSRE is designed to correctly match an input speech waveform segment to an appropriate internally-stored pattern even when the input waveform segment is embedded in a longer segment of continuous speech. Jay G. Wilpon, et al., Automatic Recognition of Keywords in Unconstrained Speech Using Hidden Markov Models, IEEE Transactions on Acoustical Speech and Signal Processing, November 1990, at 1870-78; Hirohjuki Tsuboi, et al., A Real-Time Task-Oriented Speech Understanding System Using Keyword Spotting, IEEE Transactions on Acoustical Speech and Signal Processing, September 1992, at 197-200.
In describing this invention, the term "discrete speech recognition engine" or "DSRE" shall be identified with the basic whole-word/phrase implementation, although other modifications such as the above could be employed as the technology improves.
A DSRE for which a user can specify some or all of the lexical items (speech segments) which the DSRE must differentiate should also be able to compute (N2 -N) distance measures between the N internal models corresponding to these lexical items: { A1, A2!, A1, A3!, . . . , A2, A3!, A2, A4!, . . . , AN-1, AN!} since this set of internal distance measures can be used to determine whether the internal waveforms are separated sufficiently by the DSRE analysis scheme. For example, in using a DSRE for control purposes, the user might desire the English commands "go" and "no" as lexical items. However, the analysis scheme used may not distinguish adequately between the internal samples representing these two speech segments; that is, the distance measure A(go), A(no)! might be very small. The user could then substitute alternate terms with a roughly equivalent meaning, such as "start" or "proceed" for "go" or "negative" for "no."
In the applications mentioned above, there is at any one time a specified set of allowable utterances which the DSRE is required to differentiate. However, this set of allowable utterances can be made changeable by the computer system in which the DSRE is embedded. For example, at one time the specified set might be based on the voice and selections of a first user while at another time it might be based on a second user. Unlike the system disclosed below, however, in such previous systems it is the case that, given the set active at any specific time, the speaker can choose any utterance from the set, with all such utterances equally valid.
When used for language learning, a conventional DSRE has a number of significant restrictions:
(1) The DSRE can only respond to a predetermined set of isolated words, phrases, or sentences. The computer program considers a sample phrase or sentence as a complete "word," and the program does not analyze linguistically the sample waveform X into component meanings.
(2) The vocabulary, though often programmable by the user to some extent, must be very limited in size to obtain good performance in a speaker-independent application. For example, a vocabulary of 100 words can strain the capabilities of the typical DSRE designed for a personal computer, however, a total vocabulary of that size would be restrictive for language instruction, especially if each complete phrase or sentence to be recognized must be considered a separate "word."
(3) To minimize errors and unrecognized speech segments, speaker-independent DSREs require the speakers to already know the language well enough to produce a voice pattern that matches the voices used to create the internal samples of the computer program. Thus, if a student first learning a new language used a conventional DSRE in a manner consistent with the present state-of-the-art, the computer program would often be unable to properly recognize the students' sample speech waveforms. This inability cannot be readily cured by the use of a speaker-dependent DSRE trained using the unselected speech patterns of the individual student or by the use of a narrowly adaptive DSRE, as defined above. Though strong speaker-dependence would reduce identification errors and unrecognized speech segments, it would not be pedagogically effective, since it would tend to build the mistakes of the student into the teaching program.
(4) To achieve near-real-time performance, it is necessary for a DSRE to ignore many aspects of the input speech waveform that would normally be considered important to good pronunciation. For example, variations in voice pitch are usually largely ignored in DSREs designed for the recognition of spoken English, because these variations are not very important in signaling differences in word meaning for the English language. (This is not true for Mandarin Chinese and certain other languages.) Also, such programs tend to differentiate poorly between certain close-sounding consonants or vowels and, in order to make the DSRE less sensitive to the rate-of-speech, current analysis schemes ignore many durational features of the individual sounds or words, even though such features may be important to the phonology (pronunciation patterns) of the language.
A problem considered by the present apparatus and method is that of employing a DSRE having some or all of the above limitations as a component in an interactive system for teaching or improving oral language skills. In particular, this application presents an apparatus and method for using a DSRE having such limitations to perform speech segment recognition, speech understanding, and speech analysis functions useful for the improvement of oral language skills.
With randomly accessed, good quality audio and video production (including still and animated graphics), a personal computer (or a remotely accessed file server of a larger computer) becomes a potentially powerful tool for language learning. However, to effectively teach or improve oral production skills, a computer system must be able to emulate the essential speech reception skills of a human listener skilled in the language. Optimally, a computer-based system used for language learning must exhibit the following properties:
(1) Recognition. The system should consistently recognize or identify the word or words spoken by the learner, even when given a marginally accurate production, just as a parent understands a child when it is learning it's first language.
(2) Understanding. The system must reliably decipher the intended meaning of the words, phrases, or sentences that are recognized.
(3) Speech analysis. Optimally, the system should also be able to meaningfully discriminate between properly formed and deficient productions.
(4) Correction. The system should also provide meaningful correction for certain types of deficient production.
All four elements are desirable in an effective interactive learning program. The recognition and understanding functions serve the important role of encouraging further production by enabling the learner to interact orally in the new language. However, recognition and understanding alone do not necessarily shape correct oral language skills. In fact, a computer with better recognition and understanding capabilities can be a poorer teacher of proper production skills, because poor production will more often be rewarded by understanding. In practice, an error in recognition or understanding is desirable in the case of a strongly deficient production, since these nonmatches should lead a student to suspect a need for speech production improvement.
In the proposed system, consistent recognition is accomplished by, at each step of the learning program, defining and limiting the recognition decision to certain allowable responses that form a subset of a total vocabulary of words and phrases and are mutually discriminable by the DSRE used to the extent required by the pedagogical objectives of the learning program.
In the proposed system, a correct recognition decision is linked to a correct meaning by, at each step of the learning program, making available to the learner by auditory or visual means both the proper pronunciation of each of the allowable responses and the meaning of at least the correct or appropriate allowable responses. It will usually be advantageous to also make available to the user the meaning of incorrect or inappropriate allowed responses. However, this may not always be the case. For example, some learning programs may use allowable responses that are incorrectly formed, and thus have no clear meaning.
In the proposed system, discrimination between properly formed and pronounced and deficient productions may be improved by including in the total vocabulary certain dummy responses that represent misformed or mispronounced versions of certain properly formed and pronounced responses in the subset. These dummy responses could be used to augment the subset of allowable responses for the purposes of discrimination by the DSRE, but might not be presented to the user as responses alternatives.
In the proposed system, corrective feedback may be accomplished by requiring a better production for an overt recognition decision by the system, even when the intended speech segment of the production is potentially identifiable within the subset of allowable responses by the DSRE used, or by using more complex schemes of auditory or visual feedback to the user as to the proper pronunciation, syntax, etc.
Accordingly, it is an object of this invention to provide an apparatus and method for extending the capability of a computer speech recognition program to reliably recognize, understand, and analyze a large vocabulary of words and phrases for the purposes of teaching the comprehension and oral production of those words and phrases. It is another object of the invention to add substantial speech correction capability to such a program. It is a more specific object of this invention to provide a method for employing a computer subprogram that matches the oral response of a learner to patterns corresponding to a set of prespecified speech segments in order to teach oral language skills. In this method, the computer may supply information to the learner such that some of the allowable responses are correct and some are incorrect, with the sets of correct and of incorrect responses judiciously selected to teach some aspect of the new language.
FIG. 1 is a diagram of prior art interactions between a computer and a user.
FIG. 2 is a diagram of a preferred embodiment of a speech recognition method.
FIG. 3 is a diagram of a preferred embodiment of a speech recognition method with dummy responses.
FIG. 4 is a diagram of a preferred embodiment of a speech recognition apparatus.
As the solid arrows in prior art FIG. 1 indicate, schemes for language instruction include a computer 57 which communicates to a user 56 by either visual 51 or auditory 52 means, while the user 56 normally responds to the computer using a manual device 53, such as a keyboard, computer mouse, trackball, joystick, or touch screen. Using these communication modalities, interactive activities such as games, stories, or practice drills can be devised to teach or improve comprehension skills in the aural (listening) and visual (reading) modalities and improve orthographic production skills in the manual (writing or typing) modality.
For the improvement of oral production skills (speaking), however, the user 56 must be able to talk to the computer 57 in a meaningful way, as indicated by the dashed arrow oral link 54 in FIG. 1. FIG. 1 also includes an electronic visual link 55 from the user 56 to the computer 57 that would be appropriate if the language production skills to be learned were for a manual (sign) language. Before this apparatus and method was created, oral input to a computer for the purpose of language learning has been essentially limited to a record-playback function. This record-playback function mimics the operation of a tape recorder, except that the random-access memory of a computer facilitates playing back voice productions in close temporal proximity to productions of the same material pre-recorded in the computer's memory. Thus, students can easily compare their own pronunciation with the "computer's," but students must still rely on their own subjective perception of how close their pronunciation is to the model. Additionally, a record-playback function alone does not permit the interactive interplay between the student and the computer, because the computer system does not react differentially to the linguistic or semantic content of the user's voice input.
A. Implementing Understanding with a Conventional DSRE
FIG. 2 illustrates a preferred embodiment of the speech recognition method for learning that uses a conventional DSRE computer subprogram 10. The full vocabulary 1 of words, phrases, or sentences to be taught is partitioned into a multitude of possibly overlapping subsets, exemplified by 2a, 2b, and 2c. Each subset 2a, 2b, 2c contains vocabulary items distributed in number and pronunciation such that at least some of the individual words, phrases, or sentences in the subset are readily differentiable from others in the subset by the DSRE 10 used.
At each step in the learning program, a learning program manager 60, which can be a computer program, provides auditory or visual information to the user that defines at least one correct or appropriate oral user response, including at least one such correct or appropriate response that is in at least one of the subsets, and at least one incorrect or inappropriate oral response that is in the same subset and readily differentiable from at least one of the correct responses in the subset. This defining information, which may be, for example, in the form of a question, game, puzzle, exercise drill, or simulated conversation, is presented by means of a visual display device 4, which can be a computer monitor, by path 62, or an audio reproduction device 40, which can be an amplifier and loudspeaker or headphones, by path 63.
Further, at each step in the instructional program for which an oral response is required from a user 26, a subset selection mechanism 3, controlled by learning program manager 60 (path 61), chooses one of the subsets, exemplified by 2a, that contains at least one correct or appropriate oral response and certain other incorrect or inappropriate responses. This subset is said to contain the allowable responses for that program step.
The DSRE 10 then receives, as an input 25, an identification of the current subset S (currently subset 2a in FIG. 2) of allowable responses and places each oral response from the user 26, as obtained by a transducer such as microphone 9, into one of at least three categories according to the DSRE's evaluation of the student's response:
1. judged to match a response in the chosen subset with a correct meaning, path 5, wherein the computer goes to the next step of the language learning program, path 11, as controlled by learning program manager 60;
2. judged to match a response in the chosen subset with an incorrect meaning, path 6, wherein the computer can give a correction, path 12, which can either identify for the user the reason that the response was incorrect or inappropriate or merely identify the response as incorrect, and either go to the next step of the language learning program, path 11, or repeat the same step, path 15, as determined by the learning program manager 60; or
3. judged to not match any response in the chosen subset, path 7, wherein the computer can notify the student that it did not understand the student's response, path 13, repeat the program step, path 15, and allow the student to present a new response as controlled by learning program manager 60.
To improve performance, the responses in the chosen subset S can be selected so that the allowable correct responses are each separated from each allowable incorrect response by a large distance measure. Thus, in this preferred embodiment, the paradigm under which the DSRE is used is formed such that the allowable incorrect responses are a relatively small set, each member having a high distance measure from each allowable correct response, though not necessarily from the other incorrect responses.
For example, when asking "Which item on the screen! is a fruit? " (when teaching English), a pear might be presented on the screen along with a glass of milk and a chicken, rather than a glass of milk and a bear because "pear" and "bear" are phonetically similar. If the learning paradigm, as embodied in the program manager 60, does not require differentiation between the incorrect responses (as when the correction is "No, that is not correct."), for a correct response of "the apple", incorrect responses could be "the beer" and "the bear". Although a typical DSRE may calculate a small distance measure between these incorrect responses, both incorrect responses would be readily differentiable from the correct response. However, if the learning paradigm requires a knowledge of which incorrect response was chosen, (as when the correction is "No, that is a xxxx"), then the distance measure between the incorrect responses must also be large. Thus under such a paradigm, if the correct response is "the apple," the alternate incorrect responses "the bear" and "the beer" should not be presented simultaneously.
Likewise, if the learning paradigm does not require a knowledge of which, of more than one, correct answer is produced by the user (as when there are two pieces of fruit on the screen and either "apple" or "pear" would be correct, and the computer's response to a correct choice is "Yes, that's a fruit."), then the distance measures between the correct responses need not be large. But if the computer's response depends on which correct response is spoken, the distance measures between the correct responses must also be large. (For example, when either "a pear" or "an apple" is correct and the computer's response is "Yes, that's a pear." or "Yes, that's an apple".)
In a language learning situation, it is important that meanings of at least the correct allowable responses be made available to the student, so that the student can restrict his intended response to the meanings of the responses within the set. Thus, to use the example above, it is important that the student does not intend to say "bear" when the correct response is "pear" and allowable incorrect responses are only "chicken" and "milk", since the word "bear" is likely to be accepted by the DSRE as a correct response "pear". Thus, a preferred embodiment of this invention includes means for providing visual and/or auditory information that makes clear the meanings of at least the correct responses that are included in chosen subset S. This information can be either given automatically or at the optional request of the student. In a preferred method, a representation of the contents of S (currently subset 2a in FIG. 2) is transmitted through path 16 to the visual display device 4 or through path 17 to the audio reproduction device 40.
In a preferred embodiment, providing to the user the available or allowable responses also includes some form of modeling of the proper pronunciation of the allowable responses. This can be, in part, pronunciation examples as aural modeling provided through audio reproduction path 17 and can include visual displays, such as phonetic spelling, explanatory graphic displays, or images of a speaker's mouth which make the correct pronunciation clearer. The aural modeling can have at least two forms: exhaustive or selective.
In exhaustive modeling, all response alternatives are presented aurally, usually in the context of the question or request: "In Japan, what do most people drink--milk, tea, or coffee?" or "Do you want to turn to the left, or to the right?" The response alternatives are underlined.
In selective modeling, the response alternatives can be presented graphically or iconically on the screen. The question or request may or may not include the alternatives. For example, the following questions do not contain the response alternatives: "In Japan what do most people drink?" or "Which way do you want to turn?" The student can then hear prerecorded examples of proper pronunciations of any of the alternatives by a selection procedure. This selection procedure may consist of clicking with a mouse on the appropriate icon. For example, for the first question, the student could select a picture of a glass of milk, tea, or coffee. Or, in the second question, the student could select a diagram of arrows going to the right or to the left. An alternate selection procedure could consist of an appropriate request phrase that is readily discriminable by the DSRE. For example, the milk, tea and coffee can be labeled with the numerals 1, 2, and 3, and the selection procedure consist of the student speaking the appropriate number in either the target language or the student's native language.
Exhaustive and selective modeling can be combined, and it should be possible for the user to hear an aural model repeated. Because it does not stress the user's auditory memory greatly, exhaustive modeling allows a larger set of alternatives to be used than does selective modeling. Thus, exhaustive modeling with a small set of alternatives could be used for beginners or for younger children, with selective modeling used more with older, more advanced students.
According to this method, the mechanism for subset selection 3 can be programmed so that at each language learning program step, there is a specific static subset prepared for each question asked by the computer, or the subset selection mechanism 3 can be such that the computer program dynamically selects one or more of the items to be in the subset 2a according to some probabilistic rule. Thus, during a dynamic selection, alternative incorrect responses for a correct response of "pear" could be chosen randomly from all internal waveforms of full vocabulary 1 for which the respective distance measures from the word "pear" are adequately large.
It is also envisioned that there will be some learning program steps under this method for which there will be no clearly incorrect or inappropriate responses, but rather at least two appropriate allowable responses which must be differentiated. An example of this type of interactive language learning activity is a maze, which must be traversed under oral directions in the target language (such as "go left", "go right", "go forward", "turn around", etc.).
B. Implementing Correction with a Conventional DSRE
There is a certain amount of oral language correction inherent in an "understanding" paradigm, especially when the criterion level for acceptance is made high. This type of correction is especially strong for syntactic errors (as differentiated from phonological errors). Thus, a user who says "the house red" instead of "the red house" might receive a response of "I did not understand" from the computer and be invited to try again after reviewing aural models of the correctly spoken response alternatives.
Phonological errors and more subtle syntactic errors (such as a wrong article in English, or singular-plural mixing), however, will generally require more specific, targeted correction methods. In devising such methods, one must consider the severe constraints imposed by a specific DSRE, which attends to only a limited number of parameters of a speech signal. Even within the DSRE's parameters, the DSRE may average or blur distinctions in order to achieve recognition accuracy over a broad range of voice types and speaking styles.
In a preferred embodiment, shown in FIG. 3, the analysis limitations of a conventional DSRE are ameliorated by the specific nature of the pedagogical requirements for language instruction, namely, that the primary grammatical and phonological problems of learners having a specific native language background tend to be from a rather small set that is known to experienced language teachers familiar with the characteristics of the native language and the target language. For example, Japanese or Chinese speakers, when learning English, typically have difficulty with articles and singular-plural differences and substitutions between "l" and "r" sounds. English speakers, when learning a tone language such as Mandarin Chinese, have difficulty with word intonation patterns.
The preferred embodiment of FIG. 3 accounts for these specific pedagogical requirements by including in the speech recognition apparatus and method-for-learning dummy internal waveforms in the following manner:
(1) Specific language problems are determined that are both relevant to the language background of the user and discriminable by the DSRE used. The term "discriminable" here implies that the DSRE is capable of providing a sufficiently large distance measure between the proper production and typically misspoken productions. The misspoken productions may or may not have their own meaning in the language and may or may not be presented to the user as response alternatives by path 62 or 63.
(2) Misspoken productions are added as a set of separate internal waveforms 1' to the full vocabulary 1, to produce augmented vocabulary 1". The subset selection mechanism 3 would then select a subset 2a" of the augmented vocabulary 1" that contains both a subset of proper productions 2a and a subset of misspoken productions 2a'. The DSRE would be trained to recognize misspoken productions just as it recognizes proper productions.
(3) When a student's response, as obtained by a transducer such as microphone 9, is judged to by the DSRE 10 to match a "dummy" internal waveform from misspoken subset 2a', path 8, the language learning program would treat the student's response either simply as an unrecognized response ("I did not understand your response") 14a or as a correction, that is, an incorrect response of a particular type ("You have said walk instead of walks.") 14b, depending on the pedagogical objective.
These dummy categories would have the effect of sharpening the discrimination of the DSRE along specific dimensions that are important to the learning situation. Thus, this speech recognition method makes optimal use of the discrimination capacity of any particular DSRE. With the increasing sophistication of real-time DSREs, the range of possible corrections will increase accordingly.
C. Augmenting DSRE Discrimination Capability
As shown in FIG. 4, when aspects or parameters of speech in the target language are not discriminable by a conventional DSRE, the language learning program decision mechanism or algorithm 70 of this invention can include separate, parallel augmentative analysis schemes for those aspects or parameters, the output of which are advantageously combined with the output of the DSRE for the purpose of making the recognition decision 71.
A DSRE is most advantageously constructed so as to efficiently extract and analyze the features of the speech signal that carry the most linguistic information in the language or languages of interest. This is especially true if the DSRE is to be used for real-time analysis, as is necessary for the interactive applications described above. As a particular example, a DSRE optimally designed for the real-time analysis of English words and phrases may not analyze the intonation patten of the voice speech input, nor other aspects of sentence stress, such as voice intensity, overall spectral quality (relative strength of higher frequency harmonics), and relative segment duration, because these elements are not very important in differentiating English words and short phrases. Intonation, however, is an important feature for differentiating between words in some Asian languages, such Mandarin Chinese.
Also, if the DSRE is to operate in a speaker-independent mode, the details of the vowel quality used by the speaker cannot be made a significant factor in the recognition decision, since these details can vary greatly between speakers of the language and depend on factors such as dialect, age, health, and emotional state. For example, the presence or absence of a nasal quality to the vowels can be affected by all these factors, but nasal quality would not be linguistically significant in English, while it is important in French. Therefore, if a DSRE of this type is used for language training, and especially if the language to be taught is not the language for which the DSRE was designed for, it can be advantageous to include other voice analysis mechanisms which operate in parallel with the DSRE, and the output of which are conjoined with the output of the DSRE, in order to make a final recognition decision. This arrangement is illustrated in FIG. 4, with three augmentative analyzers 20, 21, 22 shown.
Parallel augmentative analyzers 20, 21 such as intonation analyzers and voice spectral quality analyzers can operate either from the same acoustic voice input 30 as the DSRE 10, or parallel augmentative analyzer 22 can operate from another input 31. Such other inputs could include an electroglottograph or throat microphone, both of which can be used to accurately measure intonation, a nasal vibration or airflow monitor to monitor nasality, or an oral airflow monitor which measures the degree of aspiration of, and aids in differentiating between, plosive consonants such as "b" or "p".
Parallel augmentative analyzers also can be enabled selectively by the computer program, depending on the target language and target language features and the level of production accuracy required by the program.
D. Combining Language Instruction with the Development of other Cognitive and Reasoning Skills
The method described above teaches oral language skills by inducing a dialogue between the computer and the student involving the language skill to be learned or improved. This dialogue can be advantageously constructed so as to develop other cognitive or reasoning skills as the subject matter of the language exchange. For example, a dialogue about locations and directions could be constructed so as to also teach geography and map-reading skills. A game involving the computation of arithmetic sums could be used to teach mathematical skills in addition to teaching the associated language.
Combining language learning with other cognitive or reasoning challenges is generally considered advantageous in language instruction pedagogy, in that the language is treated as a communication tool and not just a skill to be learned for its own sake. Thus, the expansion of the method described herein to combine language instruction with the teaching of other skills should be considered within the scope of this disclosure.
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|Classification aux États-Unis
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Owner name: SYRACUSE LANGUAGE SYSTEMS, NEW YORK
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:ROTHENBERG, MARTIN;REEL/FRAME:007391/0354
Effective date: 19950314
|18 juil. 2001
|Fee payment
Year of fee payment: 4
|19 oct. 2001
|31 aoűt 2005
|Maintenance fee reminder mailed
|10 févr. 2006
|Lapse for failure to pay maintenance fees
|11 avr. 2006
|Expired due to failure to pay maintenance fee
Effective date: 20060210


text:
We're not saying how, but we got hooked up with the beta of iPhone OS 3.0. Overall, things feel about the same until you flick left that extra time and hit the Spotlight screen, which works just as advertised. It's definitely a beta, though: it's laggy all around and some things don't work, like taking a photo directly in the MMS app. We took some quick snaps, check 'em out below and let us know what you want to see in the video!
Update: Added a few snaps of the landscape keyboard in Messages and Mail, anything else?
Apple iPhone 6
Buy from $100 *
- Key specs
- Reviews • 44
- Prices
- Discussions
- Type Smartphone
- Operating system iOS (8)
- Screen size 4.7 inches
- Internal memory 16 GB
- Camera 8 megapixels
- Dimensions 5.44 x 2.64 x 0.27 in
- Weight 4.55 oz
- Released 2014-09-19
Apple iPhone OS 3.0

subset: commoncrawl


text:
Farmhouse has been remodeled and decorated with a collector's touch. Unusual and fanticiful paintings and antiques are loving placed with an artist's eye.
There is a working dairy farm across from the cornfield . Visitor friendly chickens,goats and a pet pot bellied pig will greet you near farmyard entrance. Dawn views of rolling hills and distant water are awesome.
Breakfast was delicious and elaborate. Eggs cooked to order. Abundant fresh fruit and berries.
Comfortable bed, quiet and open access to living space, lounge and huge DVD collection.
You will feel lucky to get a room here. Unique experience .


text:
May 19, 2014 - Industry News
Indiana and Alabama have added the Drivewyze PreClear weigh station bypass service to 10 new locations while 12 more sites have been added in Texas, bringing the total number there to 18.
Tags: Texas, Alabama, Drivewyze, Indiana, Drivewyze PreClear, Weigh Stations
April 8, 2013 - Industry News
Hendrickson has scheduled its next round of technical suspension training for the heavy-duty transportation industry with its 11th session of the Hendrickson Vehicle Suspension Institute in the Dallas Forth Worth area in May.
Tags: Training, Texas, Suspensions, Hendrickson
January 10, 2013 - Industry News
Volvo Trucks' dealer network is now even bigger in Texas. Since January 2010, work capacity has grown 32% at Volvo Trucks locations throughout Texas.
Tags: Volvo, Dealers, Texas
We offer e-newsletters that deliver targeted news and information for the entire fleet industry.
The expert, Mark Betner from CITGO, will answer your questions
The expert, Rence Oliphant from Hendrickson, will answer your questions
The Armor Fifth Wheel is Designed for Yard Trucks
Permalite XT Features Brighter Illumination
Fuel Filter Features Durable Construction
Components Allow Upfitters to Install Camera System


text:
Miami Everglades Airboat Adventure with Transport
Read what other Viator.com travelers think about the Miami Everglades Airboat Adventure with Transport. What they loved, what they liked and what they think could be improved, it's all here to help you make the most of your next trip.
Click here for tour details, schedule and pricing
Had a great time -- next time we want to make it a longer trip!!
Had a great afternoon on the Everglades and then saw a Alligator show .Enjoyed it all .Picked up from hotel at exactly the time quoted and dropped off in Downtown Miami as requested.Well worth the cost
Great guides, airboat ride was awsum ! Busdriver was great ,we got an unexpeted tour from him on the way there! it was hot but everything was perfect even the food ! Try the Gator bites !!!!!!
Great tour. Airboat ride was only short, but it all looks the same after awhile anyway! Staff were great and we both enjoyed it all.
My wife and I really enjoyed out tour of the everglades. We plan on doing this again. The wildlife was fantastic. The tour guide was very knowledgeable and pleasant. He was a great tour guide.
great opportunity to experience everglades. transport great. staff knowledgable
Really nice day out, saw some alligators whilst out on safari, arrived back to the park and had a tour and then a show. Got to sample some alligator aswell which was delicious! Would recommend for the price
Excellent tour- booked at the last minute. We were called to finalise details, picked up and dropped off at the door. We got to see everything we wanted in a half day trip!
Perfect organisation + interesting backgroudinformation and airboat ride !
Irene C
United Kingdom
A thoroughly enjoyable trip. Very well organised.
Good all round experience with thrilling boat ride.
Great time had by all. Highly recommend
Just what we wanted. The airboat driver seemed very knowledgable and flung the boat around a bit - just enough to thrill but keeping it safe
We booked through Viator, the only thing was that we were emailed with the tour company bus name, but they arent the people that took us on the tour, so we waited at the correct time and watched all the tour buses pick up along ocean drive, then a man came and found us from an unmarked tour bus. Well we had a great time, the guy was very informative about places on our way to the Everglades, and about the history, and what to expect when we arrive at the Everglades Park, how long we had, he was also very considerate to other people on the bus, who had another trip booked after the everglades. We had a really good trip and would highly recomend using Viator, but just make sure that you know exactly which tour bus will pick you up. We would certainly not hesitate booking again, and was very good value for money.
Wonderful day, enjoyed the day out on the everglades. The staff were excellent, it was great to see nature at it best, lots of alligators, birds, flora. The alligator show was also good. Just a magical day.
Must do on everyones list.
I highly enjoyed this tour! We got an extra treat, too, since our bus driver had to pick up people along South Beach, we were given a mini "city tour" as we drove along. Being from California, this was very interesting to me. Once we arrived at the Everglades Safari Park, we instantly saw a huge aligator in the lagoon, just resting there! Our air boat tour, which lasted over 30 minutes, took us through the beautiful scenery of the Everglades. Our driver was very informative about the area, too! Along the way, we saw several aligators resting by the shore, or lazing in the water. After the airboat ride, we were treated to a short informative "show", where a man fed some aligators in a pen and told us more about them and their habits. After the show, we had about 20 minutes to browse in the gift shop or grab a snack from the cafe. All in all, this was a very ejnoyable day for me!
Great fun . Got to see 3 gaitors in the Everglades and a turtle . The talk about gaitors was vert interesting.
Really worth the money! Holding the baby aligator was an amazing experience.
Awesome tour, great customer service.
Excellent the lads loved every minute of it!!!
I had a wonderful time, the weather was nice and the tour guides were just as nice. Learned a lot about Alligator's that I didn't know. Worth doing again!
Loved this tour. So much fun. Well organised, got to see everything as listed. Very enjoyable. Thank you we would do it again!
This was the greatest adventure my family has ever had. Thanks for such a positive trip. Will recomend this to others. Great Job !!!!!
It was very good.


text:
If you think the words 'celebrity' and 'investment' are rather incongruous, you're not alone. It seems that there is a new breed of celebrity who is choosing not to blow their millions! Instead, these celebrities are seeing their wealth as a means to business enterprise. They are investing well and making wise business decisions. Let's take a look at some of these celebrity investors. (For celebrities that failed, read Celebrity Financial Failures.)
TUTORIAL: Greatest Investors
Here are some famous names you might know and their investing credentials that you might not.
Ashton Kutcher
Hollywood actor and "Two and a Half Men" star Ashton Kutcher has recently made a string of excellent investments. One of his most lucrative has been investing in Skype. In 2009, Kutcher was convinced by Silicon Valley heavyweight Marc Andreessen to risk some of his Hollywood cash on Skype. This was at a time when the web-calling service was valued at $2.75, a figure many deemed outrageously high. However, Microsoft recently purchased Skype for more than $8 billion.
He has also invested undisclosed amounts in some of the tech world's hottest start-ups, either independently or through his investment firm called A Grade Investments. Some of his best-known deals include investments in social magazine app Flipboard, location-based service FourSquare, vacation rentals web service Airbnb and photo sharing app Path. If these successes continue, perhaps in time Kutcher will be known as a venture capitalist first, and an actor second.
Justin Timberlake
In an episode that sees life replicating art, Timberlake has followed in the footsteps of social media investor Sean Parker, whom he played in the Hollywood hit "The Social Network."
Timberlake was part of a $35 million deal which saw Myspace being sold to an online ad company. Exactly how much of the $35 million Timberlake put in is unknown, but he will be playing a "major role" in the new direction of the website, which suggests it was a sizable chunk.
Justin is building quite the investment portfolio. Before this large and public deal, he invested in clothing brand William Rast, bought Mirimichi Golf course in Memphis, founded Tennman Records, invested $2 million in photo start-up Stipple and invested in Disney-acquired app maker Tapulous.
Whether Myspace will ever reclaim a stake in the online-network world remains to be seen, but Justin Timberlake will certainly be doing his best to bring some glamor to the beleaguered social networking site. (For more on startups, see Valuing Startup Ventures.)
Kim Kardashian
Kim is the daughter of the late Robert Kardashian, an American attorney who was best known as being one of the attorneys for OJ Simpson. It might be easy to dismiss the socialite and reality TV star, but it's not so easy to dismiss her latest investment.
In 2007, Kardashian and three partners founded ShoeDazzle, an online shoe and accessories website. The site now counts a reported 3 million customers, who pay a monthly fee for access to a personalized selection of shoes, jewelry and handbags every month. The website recently landed an impressive $40-million investment from venture capital firm Andreessen Horowitz. Andreessen Horowitz also happens to be invested in Facebook, Foursquare, Groupon, Skype and Twitter.
Lady Gaga
Pop singer Lady Gaga has also been putting her money into start up businesses recently. Gaga has become a major shareholder in Backplane, a platform that connects music and sports stars with their fans across various social networks. Backplane has raised approximately $1 million from a group of investors led by Google chairman Eric Schmidt. This is not Lady Gaga's first technology venture. The savvy businesswoman has also worked with game maker Zynga to release a FarmVille extension called GagaVille where players complete tasks to unlock downloads of her songs.
More and more celebrities are moonlighting as tech-investors, but will these celebrities have the necessary skills to make their businesses a success, and will we be more inclined to support a company due to its celebrity status? Only time will tell. One thing is sure, these companies will certainly be watched very carefully by the media and public alike. (To help you with investing in tech, check out A Primer On Investing In The Tech Industry.)
The Top Businesses Nurtured By Y CombinatorWe look at the top startups that were incubated at Y Combinator, one of the world's most popular business incubator firms.
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text:
- 800.878.7323
This title in other editions
The Man Who Made Vermeers: Unvarnishing the Legend of Master Forger Han Van Meegerenby Jonathan Lopez
Synopses & Reviews
Publisher Comments:
It's a story that made Dutch painter Han van Meegeren famous worldwide when itand#160;broke at the end of World War II: A lifetime of disappointment droveand#160;him to forge Vermeers, one of which he sold to Hermann Goering inand#160;mockery of the Nazis. And it's a story that's been believed ever since.and#160;Too badand#160;it isn't true.
Jonathan Lopez has drawn on never-before-seen documents from dozens of archives to write a revelatory new biography of the worldand#8217;s most famous forger. Neither unappreciated artist nor antifascist hero, Van Meegeren emerges as an ingenious, dyed-in-the-wool crookand#151;a talented Mr. Ripley armed with a paintbrush. Lopez explores a network of illicit commerce that operated across Europe: Not only was Van Meegeren a key player in that high-stakes game in the 1920s and '30s, landing fakes with famous collectors such as Andrew Mellon, but he and his associates laterand#160;cashed in on the Nazi occupation.
The Man Who Made Vermeersand#160;is a long-overdue unvarnishing of Van Meegerenand#8217;s legend and a deliciously detailed story of deceit in the art world.
"In this engaging study, art historian Lopez examines — as did Edward Dolnick's Forger's Spell, published in June — the fascinating case of Han van Meegeren, a notorious Dutch art forger. Van Meegeren, who sold Hermann Goering a fake Vermeer, was convicted of collaboration; he became a folk hero for duping the Nazi leader. But according to Lopez, van Meegeren was a successful forger long before WWII, and contrary to van Meegeren's claim that he was avenging himself on the art critics who had scorned his own work, Lopez says he was motivated by financial gain and Nazi sympathies: 'What is a forger if not a closeted bermensch, an artist who secretly takes history itself for his canvas?' Lopez asks provocatively. The author gives a vivid portrait of the 1920s Hague, a stylish place of 'mischief and artifice' where van Meegeren learned his trade, and brilliantly examines the influence of Nazi Volksgeist imagery on van Meegeren's The Supper at Emmaus, part of his forged biblical Vermeer series. Lopez's writing is witty, crisp and vigorous, his research scrupulous and his pacing dynamic. 88 b&w photos. (Sept.)" Publishers Weekly (Starred Review) (Copyright Reed Business Information, Inc.)
Jonathan Lopez recasts an anti-fascist folk hero as a Talented Mr. Ripley armed with a paintbrush in a new biography of a painter who famously forged Hermann Goering's Vermeer.
About the Author
JONATHAN LOPEZ's writings on art and history appear frequently in Apollo: The International Magazine of Art and Antiques, published in London. The Man Who Made Vermeers grew out of an article that originally appeared in Dutch in De Groene Amsterdammer. Lopez lives with his wife, an art historian and critic, in Manhattan
Table of Contents
Introduction and#149; A Liarand#8217;s Biography and#149; 1
Chapter One and#149; The Collaborator and#149; 11
Chapter Two and#149; Beautiful Nonsense and#149; 21
Chapter Three and#149; The Sphinx of Delft and#149; 52
Chapter Four and#149; Smoke and Mirrors and#149; 72
Chapter Five and#149; A Happy Hunting Ground and#149; 100
Chapter Six and#149; The Master Forger and the Fascist Dream and#149; 124
Chapter Seven and#149; Sieg Heil! and#149; 143
Chapter Eight and#149; Goering Gets a Vermeer and#149; 166
Chapter Nine and#149; The Endgame and#149; 186
Chapter Ten and#149; Swept Under the Rug and#149; 221
Epilogue and#149; Framing the Fake and#149; 243
Acknowledgments and#149; 249
Endnotes and#149; 257
Select Bibliography and#149; 295
Picture Credits and#149; 317
Index and#149; 323
What Our Readers Are Saying
Be the first to add a comment for a chance to win!
Product Details
Other books you might like
Related Subjects
Arts and Entertainment » Art » Forgery


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Members of the media seeking comment from the Foundation or to interview a MacArthur staff person, should email Andy Solomon or call MacArthur Public Affairs at (312) 917-3690.
March 16, 2012 - Press Release
Marjorie M. Scardino, Chief Executive Officer of Pearson, was elected to chair the 15-member Board of Directors of the MacArthur Foundation. Read More
March 13, 2012 - Press Release
The research will explore the role housing plays in the long-term health and well-being of children, families, and communities. Read More
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The Competition links designers, entrepreneurs, technologists and educators with leading business and industry organizations to build digital badge systems and explore the ways badges can demonstrate knowledge and civic opportunities. Read More
February 27, 2012 - Press Release
MacArthur today announced a $500,000 grant to the newly launched Born This Way Foundation (BTWF) to support online and on-the-road efforts to engage young people in civic life and deter bullying. Read More
February 16, 2012 - Press Release
Their missions are diverse – from protecting ecosystems to defending children's rights, from empowering girls to strengthening neighborhoods, from investigative reporting to eliminating abusive financial practices. Read More
February 8, 2012 - Press Release
MacArthur's 25-year support of conservation efforts around the world continues with three grants for global policy research and analysis projects to help inform and respond to increased pressures from development and climate change. Read More
February 1, 2012 - Press Release
Joi Ito, Director of the Media Lab at the Massachusetts Institute of Technology, has been named to serve on the Board of Directors of the MacArthur Foundation. Read More
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MacArthur awarded $504,000 in new grants to 12 Chicago arts and culture organizations to conduct collaborations with arts groups in nine countries. Read More
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Forget password?
Remember Me
After the band's debut release in 2010 Dreams & Bones charted on CMJ stations the band hit the road playing over 150 shows in their first 18 months together. Amidst regional touring Model Stranger spent the following two years in and out of the studio working on songs and additional material for their follow up release.
Taking less of a live approach into the studio yielded exciting results as the band made a point to explore a more "Model" side of their musical sensibilities on their 2013 release, The Changing Score.
An additional EP Imitation Act showcasing the "Stranger" side of their palette was released in February of 2015. The band is currently touring in support of Imitation Act and will be heading into the studio later this year to begin work on a full length release.
Model Stranger – made up of Stephen Francis (vocals/guitar), Kevin James (Bass) and Vincent Joseph (Drums) is the epitome of a DIY band. This rock trio has worked the Midwest scene very diligently with an impressive list of successful regional tours. In addition to sharing the stage with popular national acts such as Candlebox, Our Lady Peace, Local H, Neon Trees and Ours, Model Stranger has performed at famous Midwest clubs such as; The Metro, Congress Theater, Double Door, Radio Radio and Cubby Bear. Notable festival appearances include Taste of Chicago , Taste of Linclon, Oranje Indy, Guinness Oysterfest and I AM Fest.


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Oklahoma Pet Friendly Hotels & Lodging
With a classic Americana soul and a beautiful natural setting, Oklahoma has always been a great place to visit for those who love freedom, fun, and a great road trip. Route 66 crosses the state from end to end, and other routes will take you through Oklahoma's beautiful prairies, forests, and rolling farmland.
Oklahoma welcomes pets, and there are a number of great things to do here with furry loved ones. From a sightseeing trip down Route 66, to a scenic drive through the countryside, to a hiking or fishing trip, your pet is sure to get as much out of your visit as you do. Oklahoma also offers dog parks perfect for some R&R and doggie socializing; check for them in and around cities like Tulsa, Oklahoma City, Edmond, and Norman.
The Sooner State offers lots of pet friendly hotels and lodging, as well, making traveling through the state easy. From charming bed and breakfasts and cottages, to hotels and motels of every caliber, to vacation rentals, you'll find a comfortable place for both of you to lay your head after a long day of exploration.
Top 10 Pet Friendly Cities in Oklahoma
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Paul Brodie is a name that will be familiar to those old enough to remember when the majority of mountain bikes were made from steel. He's one of the founding fathers of the Canadian mountain biking scene and these days… Read more
Lady Karma
Ocean Cervélo S2
The 2015 Tour de France was wrapped up by Mr. Froome & Co, for a second time now. No surprises there, but one team that was a surprise was MTN-Qhubeka, who made history as the first African team to compete… Read more »
Skyland Cycles Road
Over the past few years, we've had the honour of previewing Paul Brodie's entries to the North American Handmade Bicycle Show. They've always astounded us by the huge amount of dedication and skill that he instills within each project.
Paul Brodie 2015 NAHBS Tourer
The North American Handmade Bicycle Show is like the Summer Solstice of the framebuilder's year, and the 2015 edition is almost upon us. This year promises to be the biggest yet and is heading to Louisville, Kentucky. For the past… Read more »
Favourite Ride: First Lookout
The Cypress, Grouse and Seymour mountains form an integral section of the Vancouver skyline, and is the year-round playground for adventurists of all disciplines. In winter, all three mountains are the destination for all snow sport enthusiasts, while the summer… Read more »
Galtani Cycling Accoutrements
You've seen them on the hands of the Fausto Coppi, Eddy Merckx and most of the world's most stylish road cyclists. The knitted mesh cycling glove is still one of the most comfortable and functional hand coverings designed for distance… Read more »
Paul Brodie and the Starley Giraffe
For the past couple of years, we've had the honour of watching Paul Brodie manufacture a highly complicated frame to be exhibited at the North American Handmade Bicycle Show. In 2012, he walked us through each step in re-building an… Read more »


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An innovative design, which uses various different navigation elements and interfaces to create a unique way to browse around the content. Worth a look!Posted in Web Design → Portfolio
Pharmaceutical company embracing the modern design style - responsive/mobile friendly as wellJames VincentPosted in Web Design → Corporate
Personal site of Craig Jamieson, an independent design professional from Johannesburg, South Africa.James VincentPosted in Web Design → Portfolio
A superb interface for a hotel reservation app that was designed with material design guidelines followed.Posted in Interface → iPhone App
Your FForever site is a customized all-in-one solution to enhance the entire wedding experience.James VincentPosted in Web Design → Portfolio
A bright and luminous audio player that's as simple as it can possibly be.Posted in Interface → Element
Creative and unique free Christmas Icons from Icons Mind!Icons MindPosted in Interface → Element
A beautifully simple concept, perfectly executed.Posted in Branding → Logo
A portfolio site for a design agency that's transforms research and insight into memorable web design, development and brand strategy based out of Chicago.Posted in Web Design → Design
Tim Bennett offers web design and development in Leeds, Yorkshire, UK. Web design for devices of all shapes and sizes. Great looking websites for mobiles, tablets and desktopsJames VincentPosted in Web Design → Portfolio
Root Studio is a graphic and web design agency based in Lincoln, UK. Their site is beautiful and the animations are wonderfully engaging.Tom BradleyPosted in Web Design → Portfolio
A modern, clean, and flat design for a workout app that uses space really effectively. I particularly like the typeface used and the intuitive layout.Posted in Interface → iPhone App
I love the symmetry of this logo and the use of primary colours to make an impact.Posted in Branding → Logo
The portfolio and blog of London-based front-end developer Andy Walpole. Hand-coded with SASS, AngularJS and NodeJS, the website is fully responsive with subtle CSS3 animation giving some key sections an extra visual depth.Andy WalpolePosted in Web Design → Portfolio
I'm Adam Marsden, a Web Designer & Front-end Developer. I make the internet a better looking place, building beautiful modern websites using HTML + CSS.Adam MarsdenPosted in Web Design → Portfolio
A simple yet memorable logo for a political party.Posted in Branding → Logo
Providing a fresh and innovative approach to promotional marketing and design, this site perfectly mirrors the aims of the agency.Joseph BanksPosted in Web Design → Corporate
A beautifully simple icon set that would work perfectly in a wide variety of situations.Posted in Interface → Element
A simple and clean design for a flight booking interface. However, the slightly abstract date selector might be a little cumbersome.Posted in Interface → Web App
A simple brand identity that's minimal yet memorable.Posted in Branding → Logo


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Mending bald eagle nearing release
Wounded American bald eagle healing, hopefully released by holidays
4:02 PM, Nov. 1, 2012
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Mending bald eagle nearing release
Perched on a wooden beam inside a pre-release conditioning cage at Back To The Wild, a wildlife rehabilitation and educational center, an American bald eagle calls to feeding red tail hawks in an
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All hotels in Prague, Czech Republic
1 room, 2 adults
Elisky Peskove 11, Prague, 15000, Czech Republic, 1-877-214-4288
Hotel Julian - Prague
Lowest price$79
available on 10/11/15
4-star hotel with restaurant, near Prague Dancing House
- Free buffet breakfast and WiFi
Situated in Smichov within a 15-minute walk of Memorial to the Victims of Communism, Prague Dancing House and Prague National Theatre, Hotel Julian is a central 4-star Prague hotel. You'll also be within 20 minutes of Lennon Wall and Charles Bridge.
This hotel has its own restaurant serving breakfast and dinner where you'll find a selection of items to try. Guests wishing to enjoy a drink will surely want to visit the bar/lounge.
This hotel has its own restaurant serving breakfast and dinner where you'll find a selection of items to try. Guests wishing to enjoy a drink will surely want to visit the bar/lounge.
A spa tub and a sauna are among the leisure facilities on offer. Free WiFi is provided so you can check your in-box whenever you like.
Main amenities
- 33 guestrooms
- Restaurant and bar/lounge
- Rooftop terrace
- Spa tub
- Sauna
- Conference center
- Airport shuttle
- 24-hour front desk
- Coffee/tea in the lobby
- Air conditioning
- Daily housekeeping
- Car rentals on site
What's around
- In Smichov
- Prague Dancing House (0.6 mi / 0.9 km)
- Prague National Theatre (0.6 mi / 1 km)
- Old Town Square (1.3 mi / 2.1 km)
- Lennon Wall (0.7 mi / 1.2 km)
- Charles Bridge (1 mi / 1.5 km)
We loved this small hotel which was out of the main tourist drag. Staff made every effort…
We loved staying in a small hotel. The staff were always so helpful. location is great -…
TripAdvisor Traveller Rating: 4.5
From 1,159 reviews
Enter dates to check prices
Hotel Info: 1-877-214-4288from $79
- Standard Single Room
- Standard Double or Twin Room
- Standard Triple Room
- Standard Twin Room
Also popular with travelers from the USA
At a glance
Key facts
Hotel size
- This hotel has 33 rooms
- This hotel is arranged over 5 floors
- Check-in time starts at 2 PM
- Check-out time is Noon
Required at check in
- Credit card or cash deposit required
- Government-issued photo ID required
Travelling with others
- Pets allowed *
- Free WiFi in public areas
- Free WiFi in rooms
- Airport shuttle (available 24 hours) *
- Train station pickup *
- Accessible parking
- Area shuttle *
In the hotel
Food and drink
- Free buffet breakfast daily
- Restaurant
- Bar/lounge
- Room service (during limited hours)
- Coffee/tea in the lobby
Things to do
- Spa tub
- Sauna
Working away
- Meeting rooms
- Conference center
- 24-hour front desk
- Tours/ticket assistance
- Limo or Town Car service available
- Dry cleaning/laundry service
- Laundry facilities
- Free newspapers in lobby
- Luggage storage
- Number of buildings/towers - 1
- Elevator/lift
- Safe-deposit box at front desk
- Rooftop terrace
- Library
- Fireplace in lobby
- Television in lobby
- Disabled parking
- Accessible path of travel
- Braille or raised signage
- Accessible bathroom
- In-room accessibility
In the room
Home comforts
- Climate control
- Air conditioning
- Minibar
- Coffee/tea maker
- Iron/ironing board (on request)
Sleep well
- Hypo-allergenic bedding available
- Pillow menu
- Blackout drapes/curtains
- Soundproofed rooms
Freshen up
- Private bathroom
- Free toiletries
- Hair dryer
Be entertained
- Pay movies
- Satellite TV channels
Stay connected
- Desk
- Free WiFi
- Phone
Food and drink
- Free bottled water
- Daily housekeeping
- In-room safe
Special features
DiningJulian Restaurant - This family restaurant serves breakfast and dinner. Guests can enjoy drinks at the bar.
Hotel Julian - Prague's small print
Optional extras
Late check-out can be arranged for an extra charge of CZK 500
Self parking costs CZK 360 per night
Rollaway beds are available for CZK 650 per night
Pets are allowed for an extra charge of CZK 250 per stay
Airport shuttle service is offered for an extra charge
Area shuttle service is offered for an extra charge
We have included all charges provided to us by this hotel. However, charges can vary, for example, based on length of stay or the room you book.


text: I was traveling alone to attend a wedding and was a little nervous doing this all solo. When I arrived at the airport, I called Ahmed for the shuttle to the hotel. This was a wonderful free service the hotel offered. I was too early but he said he did not want me to wait for the next shuttle and would send Mustafa to get me. I could not believe their care and concern and that they would send their shuttle for just one person. From that moment on, I knew this was going to be a great place to stay. All my concerns of traveling alone were washed away. I did meet up with some family later on and we all commented that this hotel made you feel so welcome. It was a wonderful experience. The rooms were large and well furnished. The staff so helpful and friendly. I would stay there again.


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